Volume 10, Issue 1 (March 2011)                   JIRSS 2011, 10(1): 45-61 | Back to browse issues page

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Fakoor V, Jomhoori S, Ganjeali A. Density Estimators for Truncated Dependent Data. JIRSS. 2011; 10 (1) :45-61
URL: http://jirss.irstat.ir/article-1-120-en.html
Abstract:   (8366 Views)
In some long term studies, a series of dependent and possibly truncated lifetime data may be observed. Suppose that the lifetimes have a common continuous distribution function F. A popular stochastic measure of the distance between the density function f of the lifetimes and its kernel estimate fn is the integrated square error (ISE). In this paper, we derive a central limit theorem for the integrated square error of the kernel density estimators in the left-truncation model. It is assumed that the lifetime observations form a stationary strong mixing sequence. A central limit theorem (CLT) for the ISE of the kernel hazard rate estimators is also presented.
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Received: 2011/10/22 | Accepted: 2015/09/12 | Published: 2011/03/15

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